Research on Labour Market Efficiency Evaluation Under Impact of Media News Based on Machine Learning and DMP Model

The labour market constitutes a pivotal element of the national economy, exerting a profound influence on the health and stability of the broader economic system. In recent years, the role of media journalism in the dissemination of information has increased significantly, with a notable impact on supply-demand and price fluctuations in the labour market. By analysing the impact of media news, it is possible to gain a deeper understanding of, and insight into, the dynamics of the labour market. This study employs a combination of machine learning techniques and a dynamic stochastic general equilibrium model (DMP model) to assess the influence of media news on labour market efficiency. The use of machine learning algorithms enables the processing and analysis of substantial quantities of media news data, facilitating the extraction of sentiment and topic changes. The DMP model is employed to simulate the matching process in the labour market and evaluate the impact of news on the efficiency of matching job seekers and job openings. The study demonstrates, through experimental analysis, the disparate impacts of media news on the labour market across different economic cycles, and validates the efficacy and practicality of the model.